13th October 2025
We’re continuing our special six-part Humanitarian AI series podcast, building on the groundbreaking research conducted by the HLA in partnership with Data Friendly Space (DFS). We’re shining a spotlight on the experts you’ll be hearing from – read on to learn about the work and perspectives of Deogratius Kiggudde.
Meet Deogratius Kiggudde – a Programme Manager for the Upanzi Digital Public Infrastructure Network at Carnegie Mellon University Africa. We’re pleased that Deogratius will feature on the Fresh Humanitarian Perspectives podcast as an expert guest in episode five of the Humanitarian AI series: ‘Localising AI solutions: practitioner experiences from Rwanda.’
Deogratius joins the HLA’s Ka Man Parkinson on the podcast to share his experiences of working with open-source tech and AI within Rwanda’s hands-on innovation environment, from field deployment challenges to building communities around shared tools. In this conversation, Deogratius, who considers himself “a person of the continent,” demonstrates how implementation, governance, ethics and localisation intersect in practice from a pan-African perspective.
The podcast conversations build on findings and themes to emerge from the August 2025 report: How are humanitarians using artificial intelligence in 2025? Mapping current practice and future potential.
The humanitarian landscape is at a learning point. AI is definitely going to be a major game-changer, but only if it’s used where it’s most effectively and efficiently needed.
Tell us about your journey into humanitarian AI – what drew you to this intersection of tech, AI and humanitarian and development work and what are you working on now?
I started my career in construction design with the design of roads, buildings, and houses. During my work, I got fascinated with the use of drones in the construction industry.
This led to the establishment of the Humanitarian OpenStreetMap Team (HOT), which conducted drone mapping in Dar es Salaam, Tanzania, to support flood response planning in the city. This was my introduction to technology linked with humanitarian and development response.
For close to 8 years with HOT I was privileged to work on various mapping and disaster response projects that put me at the intersection with technology and humanitarian work, With work that that included using satellite imagery and machine learning to super charge mapping efforts and validate results in the field to using 360 cameras to map and validate on ground features using computer vision models and many more.
But it was when I got more involved in the open source movement Free and Open-Source Software (FOSS) that I became more intrigued about how I could contribute and be part of the FOSS movement.
Once I got into the movement, I got introduced to the concept and software that came to be called Digital Public Goods, software like DHIS2 (formerly District Health Information Software), OpenCRVS (open-source digital solution for civil registration, designed specifically for low-resource settings), and QGIS (free and open-source Geographic Information System).
But my understanding and knowledge of AI really propelled when I joined the Upanzi Digital Public Infrastructure Network at Carnegie Mellon University Africa, which is working and building amazing tools and platforms using AI and machine learning.
With a wide range of AI research and Engineering experts, the team is working using AI and machine learning models to strengthen the rollout and adoption of Digital ID in Ethiopia. Together with Ethiopia’s National ID Program, the team is also working on a tool called Policy Analyser.
The Policy Analyser platform uses AI chatbots that allow a user to investigate, compare, and understand Digital ID and data protection laws easily. The team is also working on developing new ways of using AI to assess and evaluate the cybersecurity landscape of Africa.
From your vantage point, what does the humanitarian AI landscape look like in 2025? What’s a key area that excites you and what’s a risk area that concerns you most?
I think for 2025, the humanitarian landscape is at a learning point. AI across all sectors is still growing, settling, and finding the most appropriate and effective need.
In the humanitarian sector, AI is definitely going to be a major game-changer, but only if it’s used where it’s most effectively and efficiently needed. It is at this time that humanitarian organisations need to really think about the pain points in their delivery processes – from logistical operations to data validation – and understand what has been their biggest hurdles in achieving their goals – and how, if possible, AI can help.
From a GIS (geographic information systems) and mapping background, I am excited about AI in the mapping geo analytics space coming more alive, making it easier for people who are less techy to get involved in the space, and easing the use of tools to make better and quicker decisions.
I am also excited about SLMs (small language models), which are models that are lighter and need less processing power than the LLMs (large language models like ChatGPT) that everyone is talking about.
I believe these models will be particularly useful in the humanitarian sector, as they enable the creation of offline and off-grid systems, which are ideal for humanitarian and conflict zones that often exhibit these environmental characteristics.
I am also excited about the agentic AI work coming through. Most of it is still in the early stages, but the work seems promising, where we shall go from just getting answers from AI about our questions, but getting digital tasks with multiple steps taken on my AI.
I do feel AI comes with risk, like bias, especially if not well-tuned, as well as over-reliance on the results the AI provides us. We should try to keep in mind that AI is just a tool that helps us make decisions and not make decisions for us.
Rwanda is a regional pioneer in terms of tech and AI enabling policies – could you tell us how this translates into on-the-ground innovation and research and how this supports your work with Carnegie Mellon University Africa?
Definitely, Rwanda is working and walking the talk of becoming a technology powerhouse on the African continent. The government is not only setting up policies, but also driving them. In some countries, working with the government can be quite tricky, but in Rwanda, they have set up an environment ripe for partnership and collaboration. They have even taken on the initiative of linking the private sector, academia, and development actors, and pushing for partnerships to go beyond just signing MOUs (Memorandam of Understanding).
The government has established a space for the Kigali Innovation City, where CMU-Africa is located, as a platform for academia and industry to innovate and collaborate physically side-by-side.
The appetite for research and innovation in the country is strong and growing; this has, for example, enabled the testing of the Upanzi Network at CMU-Africa’s opportunistic mesh rural connectivity project in Kiziba refugee Camp. This project, in collaboration with World Vision and guidance from the government, uses low-cost systems and open-source software to bring connectivity to one of the most rural areas in Rwanda.
From your technical perspective, what do you see as priority areas for AI development in humanitarian contexts over the next 12-24 months?
Over the next couple of months, I think it’s going to be a leap from the invention to the adoption because innovation only happens if adoption takes place, and adoption takes place when knowledge of the use of a platform to assist in achieving needed tasks happens. I do think, however, that the priority should be on how we can effectively utilize AI in the humanitarian context. So my opinion should be organisations should not chase to have the shiniest and most recent AI model on the planet, but rather what the models can now do for them.
What message would you like to share with Big Tech, Global North actors, and UN agencies about how regional innovation hubs like Rwanda can reshape humanitarian AI development?
Let’s invest more in learning how to use the tools effectively and efficiently by first identifying our biggest pain points in achieving our missions and objectives. Once we list those pains, then let’s work out what AI can do with those tasks.
About Deogratius Kiggudde
Deogratius Kiggudde is a Programs Manager for the Upanzi Digital Public Infrastructure Network at Carnegie Mellon University Africa. He manages teams that oversee multi-country research, innovation, capacity building, and outreach initiatives across AI, cybersecurity, connectivity, digital ID, payments, data governance, and DPI implementation.
He leads stakeholder engagement in the digital sector, bringing together government, donors, the private sector, and academia through policy panels, solution demonstrations, conferences, and roundtables. He enhances partnerships and promotes delivery with user training and documentation.
Previously, he served as Senior Programs Manager for Technology and Implementation at the Humanitarian OpenStreetMap Team, where he coordinated multi-country teams, expanded a regional grant portfolio, and built impactful partnerships. He holds a BSc in Quantity Surveying, a Postgraduate Diploma in Monitoring and Evaluation, and a PMP certification.
About the report and podcast series
In August 2025, the Humanitarian Leadership Academy and Data Friendly Space launched a joint report on artificial intelligence in the humanitarian sector: How are humanitarians using artificial intelligence in 2025? Mapping current practice and future potential.
Drawing on insights from 2,539 survey respondents from 144 countries and territories, coupled with deep dive interviews, this study was the world’s first baseline study of AI adoption across the humanitarian sector.
In the next phase of our initiative, we’re releasing a six-episode podcast series featuring expert guests to build on the themes emerging from the research, including community-centred research, implementation barriers, governance and regulatory frameworks, cultural and ethical considerations, localisation, learning and training, and more. This first series will have a particular focus on the Global South and Africa due to high levels of engagement in this research from these regions.
The platform aims to promote inclusive, accessible conversations and knowledge exchange to support shared progress in the development of ethical, contextually-appropriate humanitarian AI.